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Summary: **Context:** In D18530964, we allow not set aliasAnalysis at previous registration call, and then update it to the correct one in following registration call. But its not working E2E due to those existing checks. So we want to remove or delay those TORCH_CHECKs. Here is the existing three callsites for operator.aliasAnalysisKind(): https://our.intern.facebook.com/intern/diffusion/FBS/browse/master/fbcode/caffe2/torch/csrc/jit/ir.cpp?lines=994%2C995%2C996%2C1001%2C1004 https://our.intern.facebook.com/intern/diffusion/FBS/browse/master/fbcode/caffe2/torch/csrc/jit/operator.cpp?lines=147%2C155 https://our.intern.facebook.com/intern/diffusion/FBS/browse/master/fbcode/caffe2/torch/csrc/jit/passes/alias_analysis.cpp?lines=260%2C277%2C380 **Things to check** 1. Those two checks are different. But since in original op_registration code, if options.schemaOrName_->is_right() is FALSE, we kind of convert it to FunctionSchema type, so in the read callsites, we only need to check the following: options.aliasAnalysisKind_ == AliasAnalysisKind::FROM_SCHEMA || !schema.hasAnyAliasInfo() 2. If the three callsites above are indeed needed for those checks. 3. Here we made assumptions that for reads from jit or other places, its always being called after all registrations calls are done. Trying to make sure its a valid assumption Pull Request resolved: https://github.com/pytorch/pytorch/pull/30671 Test Plan: Will update and refactor the tests soon. Differential Revision: D18784623 Pulled By: charliechen0401 fbshipit-source-id: 75edea140d0ae3e54820e1aeef010c81fe26416a
1197 lines
38 KiB
C++
1197 lines
38 KiB
C++
#include <torch/csrc/autograd/generated/variable_factories.h>
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#include <torch/csrc/jit/irparser.h>
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#include "test/cpp/jit/test_base.h"
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#include "torch/csrc/jit/custom_operator.h"
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#include "torch/csrc/jit/passes/alias_analysis.h"
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#include "torch/csrc/jit/script/compiler.h"
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#include "torch/csrc/utils/memory.h"
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namespace torch {
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namespace jit {
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inline c10::OperatorOptions aliasAnalysisFromSchema() {
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c10::OperatorOptions result;
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result.setAliasAnalysis(c10::AliasAnalysisKind::FROM_SCHEMA);
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return result;
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}
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// Fixture to set up a graph and make assertions clearer
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struct TopoMoveTestFixture {
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TopoMoveTestFixture() {
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createGraph();
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aliasDb = torch::make_unique<AliasDb>(graph);
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}
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// Nodes are named after their output.
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// e.g. "a" is an alias for "the node that outputs the value `a`"
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void createGraph() {
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graph = std::make_shared<Graph>();
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createNode("a", {});
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createNode("b", {"a"});
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createNode("c", {});
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createNode("d", {"a", "b"});
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createNode("e", {"c", "b"});
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createNode("f", {"e"});
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createNode("g", {"e"});
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createNode("h", {"g"});
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createNode("i", {"g"});
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createNode("j", {"i"});
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createNode("k", {"i"});
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createNode("l", {"a"});
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createNode("m", {}, {"l"}); // block depends on l
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createNode("n", {"m"});
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createNode("o", {"n"});
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createNode("p", {});
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createNode("q", {});
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createNode("r", {"q"});
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createNode("s", {"q"});
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graph->lint();
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}
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void createNode(
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const std::string& name,
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const std::vector<std::string>& inputNames,
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const std::vector<std::string>& blockInputNames = {}) {
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std::vector<Value*> inputs;
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for (const auto name : inputNames) {
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inputs.push_back(nodes.at(name)->output());
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}
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auto node = graph->appendNode(graph->create(prim::AutogradZero, inputs));
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node->output()->setDebugName(name);
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nodes[name] = node;
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if (blockInputNames.size() != 0) {
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node->addBlock();
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std::vector<Value*> blockDeps;
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for (const auto name : blockInputNames) {
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blockDeps.push_back(nodes.at(name)->output());
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}
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auto block = node->blocks().at(0);
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block->appendNode(graph->create(prim::AutogradZero, blockDeps));
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}
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}
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bool moveBeforeTopologicallyValid(
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const std::string& toInsert,
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const std::string& insertPoint) {
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std::function<bool(Node*, Node*)> func =
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[this](Node* toInsert, Node* insertPoint) {
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return aliasDb->moveBeforeTopologicallyValid(toInsert, insertPoint);
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};
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return moveWithChecks(toInsert, insertPoint, func);
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}
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bool moveAfterTopologicallyValid(
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const std::string& toInsert,
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const std::string& insertPoint) {
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std::function<bool(Node*, Node*)> func =
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[this](Node* toInsert, Node* insertPoint) {
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return aliasDb->moveAfterTopologicallyValid(toInsert, insertPoint);
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};
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return moveWithChecks(toInsert, insertPoint, func);
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}
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bool moveWithChecks(
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const std::string& toInsert,
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const std::string& insertPoint,
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std::function<bool(Node*, Node*)> func) {
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auto n = nodes.at(toInsert);
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auto insert = nodes.at(insertPoint);
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bool isAfter = n->isAfter(insert);
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std::vector<Node*> originalOrdering;
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Node* original = isAfter ? n->next() : n->prev();
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auto curNode = original;
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while (curNode != n->owningBlock()->return_node()) {
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originalOrdering.push_back(curNode);
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if (isAfter) {
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curNode = curNode->next();
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} else {
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curNode = curNode->prev();
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}
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}
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const auto couldMove = func(n, insert);
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// Check the graph is okay
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graph->lint();
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// If this is the picture of nodes
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// <some nodes> ... toInsert ... <some more nodes> ... insertPoint
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// ^----------^ check that these nodes haven't moved
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curNode = original;
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size_t idx = 0;
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while (curNode != n->owningBlock()->return_node()) {
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AT_ASSERT(originalOrdering[idx] == curNode);
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if (isAfter) {
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curNode = curNode->next();
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} else {
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curNode = curNode->prev();
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}
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idx++;
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}
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return couldMove;
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}
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void checkPostCondition(
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const std::string& toInsert,
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const std::string& insertPoint,
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bool after) {
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if (after) {
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AT_ASSERT(nodes.at(toInsert)->prev() == nodes.at(insertPoint));
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} else {
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AT_ASSERT(nodes.at(toInsert)->next() == nodes.at(insertPoint));
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}
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}
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std::shared_ptr<Graph> graph;
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std::unique_ptr<AliasDb> aliasDb;
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std::unordered_map<std::string, Node*> nodes;
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};
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void testTopologicalMove() {
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{
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// Check that we are removing `this`'s deps properly when we need to split
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// `this` and deps (see code for what the hell that means)
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("q", "s"));
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fixture.checkPostCondition("q", "s", false);
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}
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// Move after
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{
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// Simple move backward
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveAfterTopologicallyValid("c", "a"));
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fixture.checkPostCondition("c", "a", true);
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}
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{
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// simple invalid move backward
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TopoMoveTestFixture fixture;
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AT_ASSERT(!fixture.moveAfterTopologicallyValid("d", "a"));
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}
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{
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// doesn't actually move anything
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveAfterTopologicallyValid("f", "e"));
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fixture.checkPostCondition("f", "e", true);
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}
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{
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// move backward with multiple dependencies
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveAfterTopologicallyValid("e", "c"));
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fixture.checkPostCondition("e", "c", true);
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}
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{
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// Move backward with non-zero working set
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveAfterTopologicallyValid("k", "f"));
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fixture.checkPostCondition("k", "f", true);
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}
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{
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// Simple move forward
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveAfterTopologicallyValid("c", "d"));
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fixture.checkPostCondition("c", "d", true);
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}
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{
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// Move forward with non-zero working set
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveAfterTopologicallyValid("f", "l"));
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fixture.checkPostCondition("f", "l", true);
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}
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// Move before
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{
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// Simple move forward
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("b", "d"));
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fixture.checkPostCondition("b", "d", false);
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}
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{
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// Simple move backward
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("c", "a"));
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fixture.checkPostCondition("c", "a", false);
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}
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{
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// doesn't actually move anything
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("a", "b"));
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fixture.checkPostCondition("a", "b", false);
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}
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{
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// move forward with deps
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("f", "m"));
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fixture.checkPostCondition("f", "m", false);
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}
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{
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// move backward with deps
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TopoMoveTestFixture fixture;
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("l", "f"));
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fixture.checkPostCondition("l", "f", false);
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}
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// check that dependencies in blocks are recognized
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{
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TopoMoveTestFixture fixture;
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AT_ASSERT(!fixture.moveAfterTopologicallyValid("l", "m"));
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AT_ASSERT(!fixture.moveBeforeTopologicallyValid("m", "l"));
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AT_ASSERT(!fixture.moveAfterTopologicallyValid("n", "l"));
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AT_ASSERT(!fixture.moveBeforeTopologicallyValid("l", "n"));
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}
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// Test that moveAfter(n) and moveBefore(n->next()) are not necessarily
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// equivalent. Here, the dependency ordering is n -> o -> p. So we can't
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// move `n` after `o`, but we can move `n` before `p` (which pushes `o` after
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// `p`)
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{
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TopoMoveTestFixture fixture;
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AT_ASSERT(!fixture.moveAfterTopologicallyValid("n", "o"));
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AT_ASSERT(fixture.moveBeforeTopologicallyValid("o", "p"));
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fixture.checkPostCondition("o", "p", false);
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}
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}
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namespace {
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Node* insertIf(
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Graph& g,
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Value* condValue,
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std::function<std::vector<Value*>()> trueInst,
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std::function<std::vector<Value*>()> falseInst) {
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auto if_ = g.insertNode(g.create(prim::If, 0));
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if_->addInput(condValue); // condition value
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auto trueBlock = if_->addBlock();
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auto falseBlock = if_->addBlock();
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{
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// Mutate in true block
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WithInsertPoint g(trueBlock);
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auto outputs = trueInst();
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for (auto output : outputs) {
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trueBlock->registerOutput(output);
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}
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}
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{
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WithInsertPoint g(falseBlock);
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auto outputs = falseInst();
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for (auto output : outputs) {
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falseBlock->registerOutput(output);
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}
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}
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AT_ASSERT(trueBlock->outputs().size() == falseBlock->outputs().size());
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for (auto output : trueBlock->outputs()) {
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if_->addOutput()->setType(output->type());
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}
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return if_;
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}
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template <class Exception, class Functor>
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inline void expectThrows(Functor&& functor, const char* expectMessageContains) {
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try {
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std::forward<Functor>(functor)();
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} catch (const Exception& e) {
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if (std::string(e.what()).find(expectMessageContains) ==
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std::string::npos) {
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AT_ERROR(
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"Expected error message to contain \"",
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expectMessageContains,
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"\" but error message was: ",
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e.what());
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}
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return;
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}
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AT_ERROR(
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"Expected to throw exception containing \"",
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expectMessageContains,
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"\" but didn't throw");
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}
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} // namespace
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void testAliasAnalysis() {
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{
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auto graph = std::make_shared<Graph>();
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auto a = graph->addInput();
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auto b = graph->addInput();
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// addsB = b + b
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// c = a + b
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// a += b
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// d = c + c
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auto addsB = graph->insert(aten::add, {b, b});
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auto c = graph->insert(aten::add, {a, b});
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auto aMut = graph->insert(aten::add_, {a, b});
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auto d = graph->insert(aten::add, {c, c});
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graph->lint();
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AliasDb aliasDb(graph);
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// Can't move past a mutation of a used value
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AT_ASSERT(!aliasDb.moveAfterTopologicallyValid(c->node(), aMut->node()));
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AT_ASSERT(aliasDb.moveAfterTopologicallyValid(d->node(), c->node()));
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// b should alias to a (since they are both inputs)
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AT_ASSERT(
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!aliasDb.moveAfterTopologicallyValid(addsB->node(), aMut->node()));
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AT_ASSERT(aliasDb.moveAfterTopologicallyValid(addsB->node(), c->node()));
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graph->lint();
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}
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{
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auto graph = std::make_shared<Graph>();
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auto a = graph->addInput();
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auto b = graph->addInput();
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auto constant = graph->insertConstant(1);
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auto fresh = graph->insert(aten::rand, {constant});
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auto usesB = graph->insert(aten::add, {b, fresh});
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auto aliasesB = graph->insert(aten::select, {a, constant, constant});
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auto mutatesAliasOfB = graph->insert(aten::add_, {aliasesB, fresh});
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graph->insert(aten::add, {fresh, aliasesB});
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graph->lint();
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AliasDb aliasDb(graph);
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AT_ASSERT(!aliasDb.moveAfterTopologicallyValid(
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aliasesB->node(), mutatesAliasOfB->node()));
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AT_ASSERT(!aliasDb.moveAfterTopologicallyValid(
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usesB->node(), mutatesAliasOfB->node()));
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}
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{
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// Test moves across inner blocks
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// a = rand(1)
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// b = rand(1)
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// if True:
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// a.add_(b)
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// c = a + b
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auto graph = std::make_shared<Graph>();
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auto constant = graph->insertConstant(1);
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auto a = graph->insert(aten::rand, {constant});
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auto b = graph->insert(aten::rand, {constant});
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auto if_ = insertIf(
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*graph,
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constant,
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[&]() -> std::vector<Value*> {
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auto aMut = graph->insert(aten::add_, {a, b});
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return {aMut};
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},
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[&]() -> std::vector<Value*> { return {a}; });
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auto c = graph->insert(aten::add, {a, b});
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graph->lint();
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// we should not be able to move `c` before the if statement, since it
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// may write to `a`.
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AliasDb aliasDb(graph);
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ASSERT_FALSE(aliasDb.moveBeforeTopologicallyValid(c->node(), if_));
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}
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// test none value does not have writers
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{
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{
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auto graph = std::make_shared<Graph>();
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std::unordered_map<std::string, Value*> vmap;
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script::parseIR(
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R"IR(
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graph():
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%opt : Tensor? = prim::Constant()
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%out : Tensor = prim::unchecked_unwrap_optional(%opt)
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%ret.2 : Tensor = aten::div(%out, %out, %out)
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return (%opt, %out, %ret.2)
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)IR",
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&*graph,
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vmap);
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AliasDb aliasDb(graph);
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AT_ASSERT(!aliasDb.hasWriters(vmap["opt"]->node()));
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}
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}
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}
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void testWriteTracking() {
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RegisterOperators reg({Operator(
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"prim::creates_alias(Tensor(a) x) -> Tensor(a)",
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[](Stack& s) { return 0; },
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aliasAnalysisFromSchema())});
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const auto creates_alias = Symbol::fromQualString("prim::creates_alias");
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{
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auto graph = std::make_shared<Graph>();
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auto a = graph->addInput();
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auto b = graph->addInput();
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// aten::add(%b, %b)
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// aten::add_(%a, %b)
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// foo::creates_alias(%a)
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auto pureNode = graph->insert(aten::add, {b, b})->node();
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auto writingNode = graph->insert(aten::add_, {a, b})->node();
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auto node3 = graph->insert(creates_alias, {a})->node();
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auto aAlias = node3->output();
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graph->lint();
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AliasDb aliasDb(graph);
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ASSERT_TRUE(aliasDb.mayAlias(aAlias, a));
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ASSERT_TRUE(aliasDb.mayAlias(a, b));
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ASSERT_FALSE(
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aliasDb.writesToAlias(pureNode, std::unordered_set<const Value*>{a}));
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ASSERT_FALSE(
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aliasDb.writesToAlias(pureNode, std::unordered_set<const Value*>{b}));
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ASSERT_TRUE(aliasDb.writesToAlias(
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writingNode, std::unordered_set<const Value*>{a}));
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ASSERT_TRUE(aliasDb.writesToAlias(
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writingNode, std::unordered_set<const Value*>{a, b}));
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ASSERT_TRUE(aliasDb.writesToAlias(
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writingNode, std::unordered_set<const Value*>{aAlias}));
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}
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{
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auto graph = std::make_shared<Graph>();
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script::parseIR(
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R"IR(
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graph(%x: Tensor):
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%b : (Tensor) = aten::relu_(%x)
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return (%b)
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)IR",
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&*graph);
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auto node_iter = graph->block()->nodes().begin();
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auto relu = *node_iter;
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AliasDb aliasDb(graph);
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AT_ASSERT(aliasDb.isMutable(relu));
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}
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{
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auto graph = std::make_shared<Graph>();
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script::parseIR(
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R"IR(
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graph(%x: Tensor, %y : Tensor):
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%b : (Tensor) = aten::mul(%x, %y)
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return (%b)
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)IR",
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&*graph);
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auto node_iter = graph->block()->nodes().begin();
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auto mul = *node_iter;
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AliasDb aliasDb(graph);
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AT_ASSERT(!aliasDb.isMutable(mul));
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}
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{
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auto graph = std::make_shared<Graph>();
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std::unordered_map<std::string, Value*> vmap;
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script::parseIR(
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R"IR(
|
|
graph(%x: Tensor, %y : Tensor):
|
|
%c1 : int = prim::Constant[value=1]()
|
|
%b : (Tensor) = aten::add_(%x, %y, %c1)
|
|
return (%b)
|
|
)IR",
|
|
&*graph,
|
|
vmap);
|
|
auto add = vmap["b"]->node();
|
|
AliasDb aliasDb(graph);
|
|
AT_ASSERT(aliasDb.hasWriters(add));
|
|
AT_ASSERT(aliasDb.isMutable(add));
|
|
}
|
|
}
|
|
|
|
void testContainerAliasing() {
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%x : str = prim::Constant[value="a"]()
|
|
%y : Tensor = prim::Constant()
|
|
%a : (Tensor) = prim::TupleConstruct(%y)
|
|
%b : Dict(str, Tensor) = prim::DictConstruct(%x, %y)
|
|
%c : Tensor[] = prim::ListConstruct(%y)
|
|
return (%a, %b, %c)
|
|
)IR",
|
|
&*graph);
|
|
|
|
auto node_iter = graph->block()->nodes().begin();
|
|
auto str_node = node_iter++; // string
|
|
Node* ten_node = *node_iter++;
|
|
AliasDb aliasDb(graph);
|
|
|
|
AT_ASSERT(graph->outputs().size() == 3);
|
|
for (auto out : graph->outputs()) {
|
|
AT_ASSERT(aliasDb.mayContainAlias(ten_node->output(), out));
|
|
}
|
|
AT_ASSERT(aliasDb.mayContainAlias({ten_node->output()}, graph->outputs()));
|
|
AT_ASSERT(!aliasDb.mayContainAlias(str_node->output(), graph->outputs()));
|
|
}
|
|
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%x : str = prim::Constant[value="a"]()
|
|
%y : int = prim::Constant[value=1]()
|
|
%a : (int) = prim::TupleConstruct(%y)
|
|
%b : Dict(str, int) = prim::DictConstruct(%x, %y)
|
|
%c : int[] = prim::ListConstruct(%y)
|
|
return (%a, %b, %c)
|
|
)IR",
|
|
&*graph);
|
|
|
|
auto node_iter = graph->block()->nodes().begin();
|
|
node_iter++; // string
|
|
Node* int_node = *node_iter++;
|
|
AliasDb aliasDb(graph);
|
|
|
|
AT_ASSERT(graph->outputs().size() == 3);
|
|
// primitive values don't need to alias container
|
|
for (auto out : graph->outputs()) {
|
|
AT_ASSERT(!aliasDb.mayContainAlias(int_node->output(), out));
|
|
}
|
|
}
|
|
|
|
// Test input aliasing
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
script::parseIR(
|
|
R"IR(
|
|
graph(%x: Tensor, %y: Tensor):
|
|
%a : (Tensor) = prim::TupleConstruct(%x)
|
|
return (%a)
|
|
)IR",
|
|
&*graph);
|
|
|
|
auto node_iter = graph->block()->nodes().begin();
|
|
auto tuple_node = *node_iter;
|
|
AliasDb aliasDb(graph);
|
|
|
|
for (auto input : graph->inputs()) {
|
|
AT_ASSERT(aliasDb.mayContainAlias(input, tuple_node->output()));
|
|
}
|
|
AT_ASSERT(aliasDb.mayContainAlias(graph->inputs(), graph->outputs()));
|
|
}
|
|
|
|
// Test tuple that doesn't come from construct
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
script::parseIR(
|
|
R"IR(
|
|
graph(%x : int,
|
|
%y : Tensor,
|
|
%z : Tensor):
|
|
%3 : int = prim::Constant[value=1]()
|
|
%4 : bool = aten::eq(%x, %3)
|
|
%a : (Tensor) = prim::If(%4)
|
|
block0():
|
|
%a.1 : (Tensor) = prim::TupleConstruct(%y)
|
|
-> (%a.1)
|
|
block1():
|
|
%a.2 : (Tensor) = prim::TupleConstruct(%z)
|
|
-> (%a.2)
|
|
return (%a)
|
|
)IR",
|
|
&*graph);
|
|
|
|
AliasDb aliasDb(graph);
|
|
|
|
for (auto input : graph->inputs()) {
|
|
if (input->type() == IntType::get()) {
|
|
continue;
|
|
}
|
|
|
|
AT_ASSERT(aliasDb.mayContainAlias(input, graph->outputs().at(0)));
|
|
}
|
|
}
|
|
|
|
// test nested types
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%4 : Device? = prim::Constant()
|
|
%2 : int? = prim::Constant()
|
|
%0 : float = prim::Constant[value=1]()
|
|
%20 : bool = prim::Constant[value=0]()
|
|
%a : Tensor = aten::tensor(%0, %2, %4, %20)
|
|
%a_list : Tensor[] = prim::ListConstruct(%a)
|
|
%b : Tensor = aten::tensor(%0, %2, %4, %20)
|
|
%b_list : Tensor[] = prim::ListConstruct(%b)
|
|
%13 : (Tensor[], Tensor[]) = prim::TupleConstruct(%a_list, %b_list)
|
|
return (%13)
|
|
)IR",
|
|
&*graph);
|
|
AliasDb aliasDb(graph);
|
|
auto g_output = graph->outputs().at(0);
|
|
auto list_2 = g_output->node()->inputs().at(0);
|
|
auto list_1 = g_output->node()->inputs().at(1);
|
|
|
|
// TODO FIX assume conservatively for now
|
|
AT_ASSERT(aliasDb.mayContainAlias(list_1, list_2));
|
|
AT_ASSERT(aliasDb.mayContainAlias(list_2, list_1));
|
|
|
|
AT_ASSERT(aliasDb.mayContainAlias(list_1, g_output));
|
|
AT_ASSERT(aliasDb.mayContainAlias(list_2, g_output));
|
|
}
|
|
|
|
// simple example
|
|
{
|
|
auto graph = std::make_shared<Graph>();
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%0 : Tensor = prim::Constant()
|
|
%1 : Tensor = prim::Constant()
|
|
%13 : (Tensor) = prim::TupleConstruct(%0)
|
|
return (%13)
|
|
)IR",
|
|
&*graph);
|
|
AliasDb aliasDb(graph);
|
|
|
|
auto node_iter = graph->block()->nodes().begin();
|
|
auto first_ten = *node_iter++;
|
|
auto second_ten = *node_iter++;
|
|
auto tup_node = *node_iter;
|
|
|
|
AT_ASSERT(aliasDb.mayContainAlias(first_ten->output(), tup_node->output()));
|
|
AT_ASSERT(
|
|
!aliasDb.mayContainAlias(second_ten->output(), tup_node->output()));
|
|
|
|
std::vector<Value*> first_st = {first_ten->output()};
|
|
std::vector<Value*> second_st = {second_ten->output()};
|
|
std::vector<Value*> tup_st = {tup_node->output()};
|
|
AT_ASSERT(aliasDb.mayContainAlias(first_st, tup_st));
|
|
AT_ASSERT(!aliasDb.mayContainAlias(first_st, second_st));
|
|
AT_ASSERT(!aliasDb.mayContainAlias(second_st, tup_st));
|
|
}
|
|
{
|
|
// Test list container aliasing
|
|
auto graph = std::make_shared<Graph>();
|
|
std::unordered_map<std::string, Value*> vmap;
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%10 : bool? = prim::Constant()
|
|
%8 : Device? = prim::Constant()
|
|
%4 : int? = prim::Constant()
|
|
%0 : int = prim::Constant[value=2]()
|
|
%1 : int = prim::Constant[value=3]()
|
|
%2 : int[] = prim::ListConstruct(%0, %1)
|
|
%x : Tensor = aten::rand(%2, %4, %4, %8, %10)
|
|
%12 : int[] = prim::ListConstruct(%0, %1)
|
|
%y : Tensor = aten::rand(%12, %4, %4, %8, %10)
|
|
%22 : int[] = prim::ListConstruct(%0, %1)
|
|
%z : Tensor = aten::rand(%22, %4, %4, %8, %10)
|
|
%32 : int[] = prim::ListConstruct(%0, %1)
|
|
%fresh : Tensor = aten::rand(%32, %4, %4, %8, %10)
|
|
%foo : Tensor[] = prim::ListConstruct(%x, %y)
|
|
%43 : Tensor[] = aten::append(%foo, %z)
|
|
return ()
|
|
)IR",
|
|
graph.get(),
|
|
vmap);
|
|
AliasDb aliasDb(graph);
|
|
auto x = vmap["x"];
|
|
auto y = vmap["y"];
|
|
auto z = vmap["z"];
|
|
// Tensors x, y, and z went into a list, so they all may alias each other.
|
|
ASSERT_TRUE(aliasDb.mayAlias(x, y));
|
|
ASSERT_TRUE(aliasDb.mayAlias(y, z));
|
|
ASSERT_TRUE(aliasDb.mayAlias(x, z));
|
|
|
|
// But we know `fresh` didn't go into a list, so x, y, and z should not
|
|
// alias it.
|
|
auto fresh = vmap["fresh"];
|
|
ASSERT_FALSE(aliasDb.mayAlias(x, fresh));
|
|
ASSERT_FALSE(aliasDb.mayAlias(y, fresh));
|
|
ASSERT_FALSE(aliasDb.mayAlias(z, fresh));
|
|
}
|
|
{
|
|
// test "conservative" analysis writes to the inside of a container.
|
|
auto ops = torch::RegisterOperators(
|
|
"custom::conservative", [](torch::List<at::Tensor> in) { return in; });
|
|
|
|
auto graph = std::make_shared<Graph>();
|
|
std::unordered_map<std::string, Value*> vmap;
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%10 : bool? = prim::Constant()
|
|
%8 : Device? = prim::Constant()
|
|
%4 : int? = prim::Constant()
|
|
%0 : int = prim::Constant[value=2]()
|
|
%1 : int = prim::Constant[value=3]()
|
|
%2 : int[] = prim::ListConstruct(%0, %1)
|
|
%11 : Tensor = aten::rand(%2, %4, %4, %8, %10)
|
|
%12 : Tensor[] = prim::ListConstruct(%11)
|
|
%out : Tensor[] = custom::conservative(%12)
|
|
%ret.2 : Tensor = aten::div(%11, %11)
|
|
return ()
|
|
)IR",
|
|
graph.get(),
|
|
vmap);
|
|
AliasDb aliasDb(graph);
|
|
auto conservativeOp = vmap["out"]->node();
|
|
auto tensor = vmap["11"];
|
|
ASSERT_TRUE(aliasDb.writesToAlias(conservativeOp, ValueSet{tensor}));
|
|
}
|
|
{
|
|
auto ops = torch::RegisterOperators().op(
|
|
"uses::list",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel([](torch::List<at::Tensor> in) {
|
|
return torch::rand({2, 3});
|
|
})
|
|
.aliasAnalysis(AliasAnalysisKind::PURE_FUNCTION));
|
|
// Write to the inside of a list. Check that we can't reorder a
|
|
// print across it.
|
|
auto graph = std::make_shared<Graph>();
|
|
std::unordered_map<std::string, Value*> vmap;
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%35 : int = prim::Constant[value=1]()
|
|
%10 : bool? = prim::Constant()
|
|
%8 : Device? = prim::Constant()
|
|
%4 : int? = prim::Constant()
|
|
%0 : int = prim::Constant[value=2]()
|
|
%1 : int = prim::Constant[value=3]()
|
|
%23 : int = prim::Constant[value=0]()
|
|
%2 : int[] = prim::ListConstruct(%0, %1)
|
|
%11 : Tensor = aten::rand(%2, %4, %4, %8, %10)
|
|
%12 : int[] = prim::ListConstruct(%0, %1)
|
|
%21 : Tensor = aten::rand(%12, %4, %4, %8, %10)
|
|
%l : Tensor[] = prim::ListConstruct(%11, %21)
|
|
%24 : Tensor = aten::select(%l, %23)
|
|
%25 : int[] = prim::ListConstruct(%0, %1)
|
|
%34 : Tensor = aten::rand(%25, %4, %4, %8, %10)
|
|
%36 : Tensor = aten::add_(%24, %34, %35)
|
|
%37 : Tensor = uses::list(%l)
|
|
return (%37)
|
|
)IR",
|
|
graph.get(),
|
|
vmap);
|
|
AliasDb aliasDb(graph);
|
|
auto listUse = vmap["37"]->node();
|
|
auto internalWrite = vmap["36"]->node();
|
|
ASSERT_FALSE(aliasDb.moveBeforeTopologicallyValid(listUse, internalWrite));
|
|
}
|
|
{
|
|
// The same as above, but with a nested list
|
|
auto ops = torch::RegisterOperators().op(
|
|
"uses::list",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel([](torch::List<at::Tensor> in) {
|
|
return torch::rand({2, 3});
|
|
})
|
|
.aliasAnalysis(AliasAnalysisKind::PURE_FUNCTION));
|
|
// Write to the inside of a list. Check that we can't reorder a
|
|
// print across it.
|
|
auto graph = std::make_shared<Graph>();
|
|
std::unordered_map<std::string, Value*> vmap;
|
|
script::parseIR(
|
|
R"IR(
|
|
graph():
|
|
%38 : int = prim::Constant[value=1]()
|
|
%10 : bool? = prim::Constant()
|
|
%8 : Device? = prim::Constant()
|
|
%4 : int? = prim::Constant()
|
|
%0 : int = prim::Constant[value=2]()
|
|
%1 : int = prim::Constant[value=3]()
|
|
%24 : int = prim::Constant[value=0]()
|
|
%2 : int[] = prim::ListConstruct(%0, %1)
|
|
%11 : Tensor = aten::rand(%2, %4, %4, %8, %10)
|
|
%12 : int[] = prim::ListConstruct(%0, %1)
|
|
%21 : Tensor = aten::rand(%12, %4, %4, %8, %10)
|
|
%l : Tensor[] = prim::ListConstruct(%11, %21)
|
|
%25 : Tensor = aten::select(%l, %24)
|
|
%27 : Tensor = aten::select(%25, %24, %24)
|
|
%28 : int[] = prim::ListConstruct(%0, %1)
|
|
%37 : Tensor = aten::rand(%28, %4, %4, %8, %10)
|
|
%39 : Tensor = aten::add_(%27, %37, %38)
|
|
%40 : Tensor = uses::list(%l)
|
|
return (%40)
|
|
)IR",
|
|
graph.get(),
|
|
vmap);
|
|
AliasDb aliasDb(graph);
|
|
auto listUse = vmap["40"]->node();
|
|
auto internalWrite = vmap["39"]->node();
|
|
ASSERT_FALSE(aliasDb.moveBeforeTopologicallyValid(listUse, internalWrite));
|
|
}
|
|
}
|
|
|
|
void testWildcards() {
|
|
RegisterOperators reg({Operator(
|
|
"prim::returns_wildcard(Tensor a) -> Tensor(*)",
|
|
[](Stack& stack) { return 0; },
|
|
aliasAnalysisFromSchema()),
|
|
Operator(
|
|
"prim::writes(Tensor(z!) a) -> Tensor(a)",
|
|
[](Stack& stack) { return 0; },
|
|
aliasAnalysisFromSchema())});
|
|
const auto returns_wildcard =
|
|
Symbol::fromQualString("prim::returns_wildcard");
|
|
const auto writes = Symbol::fromQualString("prim::writes");
|
|
|
|
auto graph = std::make_shared<Graph>();
|
|
const auto a = graph->addInput();
|
|
|
|
const auto constant = graph->insertConstant(1);
|
|
const auto fresh = graph->insert(aten::rand, {constant});
|
|
const auto fresh2 = graph->insert(aten::rand, {constant});
|
|
const auto wildcard = graph->insert(returns_wildcard, {fresh});
|
|
|
|
{
|
|
graph->lint();
|
|
AliasDb aliasDb(graph);
|
|
|
|
ASSERT_FALSE(aliasDb.mayAlias(a, fresh));
|
|
ASSERT_FALSE(aliasDb.mayAlias(wildcard, fresh));
|
|
ASSERT_TRUE(aliasDb.mayAlias(wildcard, a));
|
|
ASSERT_FALSE(aliasDb.mayAlias(ValueSet{wildcard}, ValueSet{}));
|
|
ASSERT_FALSE(aliasDb.hasWriters(wildcard->node()));
|
|
}
|
|
|
|
graph->insert(writes, {fresh2})->node();
|
|
{
|
|
graph->lint();
|
|
AliasDb aliasDb(graph);
|
|
ASSERT_FALSE(aliasDb.hasWriters(wildcard->node()));
|
|
}
|
|
|
|
const auto wildcardWrite = graph->insert(writes, {wildcard})->node();
|
|
{
|
|
graph->lint();
|
|
AliasDb aliasDb(graph);
|
|
// Test writes to wildcards
|
|
ASSERT_FALSE(aliasDb.writesToAlias(
|
|
wildcardWrite, std::unordered_set<const Value*>{fresh}));
|
|
ASSERT_FALSE(aliasDb.writesToAlias(
|
|
wildcardWrite, std::unordered_set<const Value*>{fresh2}));
|
|
ASSERT_TRUE(aliasDb.writesToAlias(
|
|
wildcardWrite, std::unordered_set<const Value*>{a}));
|
|
ASSERT_TRUE(aliasDb.hasWriters(wildcard->node()));
|
|
}
|
|
}
|
|
|
|
void testMemoryDAG() {
|
|
auto graph = std::make_shared<Graph>();
|
|
const Value* aValue = graph->addInput();
|
|
const Value* bValue = graph->addInput();
|
|
const Value* cValue = graph->addInput();
|
|
const Value* dValue = graph->addInput();
|
|
const Value* eValue = graph->addInput();
|
|
const Value* fValue = graph->addInput();
|
|
const Value* gValue = graph->addInput();
|
|
|
|
{
|
|
// a <- b <- c
|
|
// b <- d
|
|
// a <- e
|
|
// f <- e
|
|
// g is by itself
|
|
MemoryDAG t;
|
|
auto a = t.makeFreshValue(aValue);
|
|
auto b = t.makeFreshValue(bValue);
|
|
auto c = t.makeFreshValue(cValue);
|
|
auto d = t.makeFreshValue(dValue);
|
|
auto e = t.makeFreshValue(eValue);
|
|
auto f = t.makeFreshValue(fValue);
|
|
auto g = t.makeFreshValue(gValue);
|
|
t.makePointerTo(b, a);
|
|
t.makePointerTo(c, b);
|
|
t.makePointerTo(d, b);
|
|
t.makePointerTo(e, a);
|
|
t.makePointerTo(e, f);
|
|
|
|
/**
|
|
* Test mayAlias()
|
|
*/
|
|
// Values should alias themselves
|
|
ASSERT_TRUE(t.mayAlias(a, a));
|
|
ASSERT_TRUE(t.mayAlias(g, g));
|
|
|
|
// Values that point to the same location should alias
|
|
ASSERT_TRUE(t.mayAlias(a, b));
|
|
ASSERT_TRUE(t.mayAlias(a, c));
|
|
ASSERT_TRUE(t.mayAlias(c, d));
|
|
|
|
// e may point to a OR f
|
|
ASSERT_TRUE(t.mayAlias(e, a));
|
|
ASSERT_TRUE(t.mayAlias(e, f));
|
|
// But a and f don't alias
|
|
ASSERT_FALSE(t.mayAlias(a, f));
|
|
}
|
|
{
|
|
// Test invalidation of memory locations
|
|
MemoryDAG t;
|
|
auto a = t.makeFreshValue(aValue);
|
|
auto b = t.makeFreshValue(bValue);
|
|
// `a` does not point to `b`
|
|
ASSERT_FALSE(a->getMemoryLocations().test(b->index));
|
|
t.makePointerTo(a, b);
|
|
ASSERT_TRUE(a->getMemoryLocations().test(b->index));
|
|
}
|
|
{
|
|
// x(y) -> x contains y
|
|
|
|
// b(a)
|
|
// c(a)
|
|
MemoryDAG t;
|
|
auto a = t.makeFreshValue(aValue);
|
|
auto b = t.makeFreshValue(bValue);
|
|
t.addToContainedElements(a, b);
|
|
|
|
auto c = t.makeFreshValue(cValue);
|
|
t.addToContainedElements(a, c);
|
|
|
|
AT_ASSERT(t.mayContainAlias(a, b));
|
|
AT_ASSERT(t.mayContainAlias(b, a));
|
|
|
|
AT_ASSERT(t.mayContainAlias(a, c));
|
|
AT_ASSERT(t.mayContainAlias(c, a));
|
|
|
|
AT_ASSERT(t.mayContainAlias(b, c));
|
|
AT_ASSERT(t.mayContainAlias(c, b));
|
|
|
|
// containers contain an element in themselves
|
|
AT_ASSERT(t.mayContainAlias(b, b));
|
|
AT_ASSERT(t.mayContainAlias(c, c));
|
|
AT_ASSERT(t.mayContainAlias(a, a));
|
|
|
|
auto d = t.makeFreshValue(dValue);
|
|
|
|
// b(a)
|
|
// c(a)
|
|
// d(b(a))
|
|
t.addToContainedElements(b, d);
|
|
AT_ASSERT(t.mayContainAlias(b, d));
|
|
AT_ASSERT(t.mayContainAlias(d, b));
|
|
|
|
AT_ASSERT(t.mayContainAlias(c, d));
|
|
AT_ASSERT(t.mayContainAlias(d, c));
|
|
|
|
AT_ASSERT(t.mayContainAlias(a, d));
|
|
|
|
// f(e)
|
|
auto f = t.makeFreshValue(aValue);
|
|
auto e = t.makeFreshValue(bValue);
|
|
|
|
t.addToContainedElements(f, e);
|
|
|
|
for (auto elem : {a, b, c, d}) {
|
|
AT_ASSERT(!t.mayContainAlias(f, elem));
|
|
AT_ASSERT(!t.mayContainAlias(e, elem));
|
|
}
|
|
}
|
|
}
|
|
|
|
void testAliasRegistration() {
|
|
{
|
|
auto registry = torch::RegisterOperators().op(
|
|
"foo::rand1",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel([](at::Tensor) -> at::Tensor {
|
|
return at::rand({2, 2});
|
|
})
|
|
.aliasAnalysis(AliasAnalysisKind::CONSERVATIVE));
|
|
const auto rand_op = Symbol::fromQualString("foo::rand1");
|
|
auto graph = std::make_shared<Graph>();
|
|
auto a = graph->addInput();
|
|
auto b = graph->insert(rand_op, {a});
|
|
AliasDb aliasDb(graph);
|
|
// Conservatively we assume there is a reference
|
|
ASSERT_TRUE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
auto registry = torch::RegisterOperators().op(
|
|
"foo::rand2(Tensor arg1) -> Tensor",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel([](at::Tensor) -> at::Tensor {
|
|
return at::rand({2, 2});
|
|
})
|
|
.aliasAnalysis(AliasAnalysisKind::CONSERVATIVE));
|
|
const auto rand_op = Symbol::fromQualString("foo::rand2");
|
|
auto graph = std::make_shared<Graph>();
|
|
auto a = graph->addInput();
|
|
auto b = graph->insert(rand_op, {a});
|
|
AliasDb aliasDb(graph);
|
|
// Conservatively we assume there is a reference
|
|
ASSERT_TRUE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
auto registry = torch::RegisterOperators().op(
|
|
"foo::rand3(Tensor(a) arg1) -> Tensor(b)",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel([](at::Tensor) -> at::Tensor {
|
|
return at::rand({2, 2});
|
|
})
|
|
.aliasAnalysis(AliasAnalysisKind::CONSERVATIVE));
|
|
|
|
const auto rand_op = Symbol::fromQualString("foo::rand3");
|
|
auto graph = std::make_shared<Graph>();
|
|
auto a = graph->addInput();
|
|
graph->insert(rand_op, {a});
|
|
|
|
// Registration time is okay, but throw exception when fetch from registration.
|
|
expectThrows<c10::Error>(
|
|
[&graph] {
|
|
AliasDb aliasDb(graph);
|
|
},
|
|
"Tried to register operator foo::rand3(Tensor(a) arg1) -> (Tensor(b)) with aliasing information in the schema but without AliasAnalysisKind::FROM_SCHEMA");
|
|
}
|
|
{
|
|
auto registry = torch::RegisterOperators().op(
|
|
"foo::rand4(Tensor(a) arg1) -> Tensor(a)",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel([](at::Tensor) -> at::Tensor {
|
|
return at::rand({2, 2});
|
|
})
|
|
.aliasAnalysis(AliasAnalysisKind::CONSERVATIVE));
|
|
const auto rand_op = Symbol::fromQualString("foo::rand4");
|
|
auto graph = std::make_shared<Graph>();
|
|
auto a = graph->addInput();
|
|
graph->insert(rand_op, {a});
|
|
|
|
// Registration time is okay, but throw exception when fetch from registration.
|
|
expectThrows<c10::Error>(
|
|
[&graph] {
|
|
AliasDb aliasDb(graph);
|
|
},
|
|
"Tried to register operator foo::rand4(Tensor(a) arg1) -> (Tensor(a)) with aliasing information in the schema but without AliasAnalysisKind::FROM_SCHEMA");
|
|
}
|
|
{
|
|
expectThrows<c10::Error>(
|
|
[] {
|
|
torch::RegisterOperators().op(
|
|
"foo::rand5",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel([](at::Tensor) -> at::Tensor {
|
|
return at::rand({2, 2});
|
|
})
|
|
.aliasAnalysis(AliasAnalysisKind::FROM_SCHEMA));
|
|
},
|
|
"Tried to register operator foo::rand5(Tensor _0) -> (Tensor _0) with AliasAnalysisKind::FROM_SCHEMA, but the schema is inferred");
|
|
}
|
|
{
|
|
auto registry = torch::RegisterOperators().op(
|
|
"foo::rand6(Tensor arg1) -> Tensor",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel([](at::Tensor) -> at::Tensor {
|
|
return at::rand({2, 2});
|
|
})
|
|
.aliasAnalysis(AliasAnalysisKind::FROM_SCHEMA));
|
|
const auto rand_op = Symbol::fromQualString("foo::rand6");
|
|
auto graph = std::make_shared<Graph>();
|
|
auto a = graph->addInput();
|
|
auto b = graph->insert(rand_op, {a});
|
|
AliasDb aliasDb(graph);
|
|
// The schema doesn't contain alias information, which means it's pure
|
|
// (meh!)
|
|
ASSERT_FALSE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
auto registry = torch::RegisterOperators().op(
|
|
"foo::rand7(Tensor(a) arg1) -> Tensor(a)",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel([](at::Tensor t) -> at::Tensor { return t * 2; })
|
|
.aliasAnalysis(AliasAnalysisKind::FROM_SCHEMA));
|
|
const auto rand_op = Symbol::fromQualString("foo::rand7");
|
|
|
|
auto graph = std::make_shared<Graph>();
|
|
auto a = graph->addInput();
|
|
auto b = graph->insert(rand_op, {a});
|
|
AliasDb aliasDb(graph);
|
|
// The schema has an alias reference
|
|
ASSERT_TRUE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
auto registry = torch::RegisterOperators().op(
|
|
"foo::rand8(Tensor(a) arg1) -> Tensor(b)",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel([](at::Tensor t) -> at::Tensor { return t * 2; })
|
|
.aliasAnalysis(AliasAnalysisKind::FROM_SCHEMA));
|
|
const auto rand_op = Symbol::fromQualString("foo::rand8");
|
|
auto graph = std::make_shared<Graph>();
|
|
auto a = graph->addInput();
|
|
auto b = graph->insert(rand_op, {a});
|
|
AliasDb aliasDb(graph);
|
|
// The schema does not have an alias reference
|
|
ASSERT_FALSE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
auto registry = torch::RegisterOperators().op(
|
|
"foo::rand9",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel([](at::Tensor) -> at::Tensor {
|
|
return at::rand({2, 2});
|
|
})
|
|
.aliasAnalysis(AliasAnalysisKind::PURE_FUNCTION));
|
|
const auto rand_op = Symbol::fromQualString("foo::rand9");
|
|
auto graph = std::make_shared<Graph>();
|
|
auto a = graph->addInput();
|
|
auto b = graph->insert(rand_op, {a});
|
|
AliasDb aliasDb(graph);
|
|
// The schema is pure, there cannot be any alias
|
|
ASSERT_FALSE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
auto registry = torch::RegisterOperators().op(
|
|
"foo::rand10(Tensor arg1) -> Tensor",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel([](at::Tensor) -> at::Tensor {
|
|
return at::rand({2, 2});
|
|
})
|
|
.aliasAnalysis(AliasAnalysisKind::PURE_FUNCTION));
|
|
const auto rand_op = Symbol::fromQualString("foo::rand10");
|
|
auto graph = std::make_shared<Graph>();
|
|
auto a = graph->addInput();
|
|
auto b = graph->insert(rand_op, {a});
|
|
AliasDb aliasDb(graph);
|
|
// The schema is pure, there cannot be any alias
|
|
ASSERT_FALSE(aliasDb.mayAlias(a, b));
|
|
}
|
|
{
|
|
auto registry = torch::RegisterOperators().op(
|
|
"foo::rand11(Tensor(a) arg1) -> Tensor(a)",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel(
|
|
[](at::Tensor t) -> at::Tensor { return t * 2; })
|
|
.aliasAnalysis(AliasAnalysisKind::PURE_FUNCTION));
|
|
const auto rand_op = Symbol::fromQualString("foo::rand11");
|
|
auto graph = std::make_shared<Graph>();
|
|
auto a = graph->addInput();
|
|
graph->insert(rand_op, {a});
|
|
|
|
// Registration time is okay, but throw exception when fetch from registration.
|
|
expectThrows<c10::Error>(
|
|
[&graph] {
|
|
AliasDb aliasDb(graph);
|
|
},
|
|
"Tried to register operator foo::rand11(Tensor(a) arg1) -> (Tensor(a)) with aliasing information in the schema but without AliasAnalysisKind::FROM_SCHEMA");
|
|
}
|
|
{
|
|
auto registry = torch::RegisterOperators().op(
|
|
"foo::rand12(Tensor(a) arg1) -> Tensor(b)",
|
|
torch::RegisterOperators::options()
|
|
.catchAllKernel(
|
|
[](at::Tensor t) -> at::Tensor { return t * 2; })
|
|
.aliasAnalysis(AliasAnalysisKind::PURE_FUNCTION));
|
|
const auto rand_op = Symbol::fromQualString("foo::rand12");
|
|
auto graph = std::make_shared<Graph>();
|
|
auto a = graph->addInput();
|
|
graph->insert(rand_op, {a});
|
|
|
|
// Registration time is okay, but throw exception when fetch from registration.
|
|
expectThrows<c10::Error>(
|
|
[&graph] {
|
|
AliasDb aliasDb(graph);
|
|
},
|
|
"Tried to register operator foo::rand12(Tensor(a) arg1) -> (Tensor(b)) with aliasing information in the schema but without AliasAnalysisKind::FROM_SCHEMA");
|
|
}
|
|
}
|
|
|
|
} // namespace jit
|
|
} // namespace torch
|